Potential of using data assimilation to support forest planning

Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However; these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool which may reduce the uncertainty and thereby improve the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way, and thus provide more accurate and up-to-date information to forest planning. In this study we refer to literature on handling uncertainties in forest planning as well as related literature from other scientific fields in order to assess the potential benefits of using DA in forest planning. We identify five major potential benefits: (i) The accuracy of the information will be improved; (ii) The information will be kept up-to-date; (iii) The DA process will provide information with estimated accuracy; (iv) Stochastic decision making can be applied, whereby the accuracy of the information can be utilized in the decision making process; and (v) DA data allows for the analysis of optimal data acquisition decisions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author